[Water Quality Characteristics and Distribution of Bacterial Communities During Thermal Stratification in the Miyun Reservoir].

As an important urban drinking water source, reservoirs are a special type of water body formed by artificial dams. Water quality of reservoirs directly affects the residents' drinking water safety. In order to reveal the characteristics of stratification and vertical changes of bacterial communities in the Miyun Reservoir, a drinking water source of Beijing, vertical stratified samples were collected during the stable stratified period of the reservoir (autumn). The vertical distribution characteristics of bacterial communities in the Miyun Reservoir were studied by using 16S rDNA terminal restriction fragment length polymorphism (T-RFLP) and quantitative PCR. Cluster analysis and multivariate statistical analysis were used to reveal the response relationships between bacterial communities and environmental factors. The results were as follows. ①The thermocline of the Miyun Reservoir was located at a water depth of 20-30 m, and the water temperature range was 15-19℃. The cluster analysis data of the seven sampled water layers were divided into an aerobic area (upper layer) and anoxic area (lower layer). The temperature, dissolved oxygen, and pH gradually decreased below 15 m. The electrical conductivity, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, and total nitrogen changed significantly after 15 m. The water quality showed obvious features in the vertical direction. ② The redundancy analysis (RDA) results showed that there were obvious vertical changes in the dissolved oxygen, pH, electrical conductivity, ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen between the aerobic and anoxic water layer. Those factors were the main environmental factors affecting the vertical distribution of the bacterial communities in the Miyun Reservoir. ③ The total bacterial number fluctuated with changes in the water depth. The Shannon-Wiener index and the number of T-RFs of bacteria in the aerobic zone were significantly higher than those in the anoxic zone, which indicates that there was significant stratification in the distribution of bacterial communities in the water of the Miyun Reservoir in autumn. This study explored the effects of water stratification on reservoir water quality and bacterial communities, and the findings provide a scientific basis for predicting water quality changes and reservoir management.

[Research of Parameter Uncertainty for the HSPF Model Under Different Temporal Scales].

Various hydrological models have been applied to the management of water resources and water quality. However, parameter uncertainty is of perpetual interest in the application of hydrological models. In this context, the HSPF model was constructed and calibrated using monthly observed stream data from 1998 to 2010 in the Chaohe River watershed, northeast of Beijing. Specifically, the sensitivity and uncertainty of the model parameters were investigated by the GLUE algorithm with the PEST platform. The major results were illustrated as follows:① the hydrological simulation shows good performance with Nash-Sutcliffe efficiency of 0.84 and 0.55 in the period of calibration and validation, respectively; ② the parameters were divided into three categories:global sensitive parameters (LZSN, INFILT, IRC, and AGWRC), regional sensitive parameters (UZSN), and non-sensitive parameters (DEEPFR, BASETP, AGWEPT, INTFW, and CEPSC); ③ strong correlations were detected within the sensitive parameters, which further involved significant negative correlations (LZSN~INFILT, INFILT~UZSN, and UZSN~AGWRC) and a positive correlation (LZSN~UZSN) and (UZSN~AGWRC); ④ the equifinality for different parameters was found in the HSPF model, indicating that parameter sets determine the simulation performance rather than individual parameters; ⑤ among various external factors, precipitation was identified as the most important condition for simulation uncertainty; and ⑥ the temporal difference in simulation performance was considered using annual, seasonal, and monthly scales with simulation precisions of 81.80%, 78.70%, and 80.56%, implying that the annual scale might be the optimal simulation period with higher accuracy. This research result is useful for the application and localization of the HSPF model.

[Dry and Wet Deposition of Atmospheric Nitrogen in Small Catchments].

Atmospheric nitrogen deposition is one of the important pathways for the transmission of terrestrial pollutants and nutrients to aquatic ecosystems. A considerable amount of nitrogen substances is delivered into the surface water environment via atmospheric deposition in the catchments, which are greatly affected by human activities, and have serious negative effects on the nutrient level and aquatic habitat environment. The Shixia Catchment north of the Miyun Reservoir was selected as study area. Samples of particulate dry and wet deposition were collected and tested. Subsequently, the variation of the atmospheric nitrogen deposition flux and factors impacting it were determined; ultimately, the contribution of atmospheric nitrogen deposition to the nitrogen budget of the catchment was estimated. The major results are as follows:① The total nitrogen deposition flux of particulate dry and wet deposition is characterized by a significant temporary variation. Regarding the total nitrogen, the ammonia nitrogen and wet deposition flux are the highest in summer and dissolved organic nitrogen is the highest in spring. However, the flux of nitrate nitrogen shows no notable seasonal fluctuation. The general trend of the particulate dry deposition flux is supreme in winter, followed by that in autumn and spring. In detail, the total nitrogen and ammonia nitrogen deposition are the largest in winter, while the seasonal variance of nitrate nitrogen appears to be less apparent. The dry deposition flux of dissolved organic nitrogen is the greatest in autumn. ② The total flux of nitrogen deposition is 43.14 kg·hm-2 in the Shixia Catchment; the wet and dry deposition flux account for 39.85% and 60.15%, respectively. ③ Rainfall and wind speed conditions are important factors impacting the atmospheric nitrogen deposition. The rainfall and rainfall intensity are negatively correlated with the wet nitrogen deposition concentration. With respect to the particulate dry deposition, the average wind speed during the monitoring period is important to ammonia nitrogen. ④ The contribution of atmospheric nitrogen deposition to the total nitrogen input in this catchment is approximately 15.09%, second only to livestock and poultry farming and rural life. The results of this study provide information that is useful for the nitrogen management in the catchment.

[Spatial Distribution Characteristics and Source Analysis of Dissolved Organic Matter in Beiyun River].

Dissolved organic matter (DOM) in aquatic ecosystems has gained wide concern because of its influence on the light attenuation, nutrient availability and contaminant transport. Human activities strongly influence the DOM of rivers in different ways, including increased agricultural activities and industrial and domestic emissions. However, recent socio-economic development with rapid urban development has significantly enhanced the discharge of sewage, and has caused high loads of DOM, which in turn pose a great risk to aquatic ecosystems. To effectively guide water management for protecting aquatic ecosystem health, it is very critical to investigate the distribution and source of dissolved organic matter in urban rivers. In this study, the distribution and source analysis of DOM in Beiyun River were evaluated, where covers the most populated area with a population of 14 million, representing the most urbanized watershed of Beijing. Since the main receiving source of the river is treated and untreated wastewater in Beijing City, the water quality is highly polluted by anthropogenic inputs. However, information on DOM of Beiyun river has not been reported. Therefore, this study can not only reveal the biogeochemistry of DOM in Beiyu River, but also provide useful implications of pollution control for similar urban rivers. The fingerprint features were extracted from the Excitation-Emission Matrix Spectrum of fluorescent dissolved organic matter (FDOM) in 23 sampling sites of Beiyun river during November 2013. Three separate fluorescent components were identified by Parallel factor analysis (PARAFAC) model, including two humic-like components (C1: 240, 300/385 nm; C2: 255, 350/400 nm) and one protein-like component (C3: 230, 280/340 nm). The results indicated that humic-like materials were generally the dominated component of FDOM, accounting for 76.18% of the average total fluorescence intensity. Positive relationships were found between the fluorescence intensity and the concentrations of some water quality indicators, such as total nitrogen, ammonia nitrogen and total phosphorus, indicating the same sources of these components. Thus, the migration and transformation of nitrogen & phosphorus could also influence the level of FDOM. The distribution of total fluorescence intensity showed a distinctly different spatial pattern. The fluorescence intensity decreased firstly along the upstream to midstream continuum, and then increased from the midstream to downstream. The FDOM in the upstream could be attributed to the industrial effluent and agricultural runoff inputs. Among the upstream to downstream continuum, the content of FDOM in the midstream was the lowest. Limited domestic pollution was suggested as the major source. In the downstream, the sources of FDOM could be interpreted as industrial, agricultural wastewater and livestock wastewater discharge. The relative abundance of protein-like materials was markedly increased in this area, indicating the sources of DOM was highly impacted by human activities. In addition, our study also concluded that the removal efficiency of DOM in wastewater plants is not very desirable, which implied that stronger support for DOM removal in sewage system is needed to alleviate DOM pollution and improve water quality.